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An opportunistic array beamforming technique based on binary multiobjective wind driven optimization method.

机译:基于二进制多目标风驱动优化方法的机会阵列波束成形技术。

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摘要

We present a novel binary version of multiobjective wind driven optimization (WDO) for emitted beamforming of opportunistic array radar, which is assumed as a multiobjective optimization problem. Firstly, the emitted signal model and objective functions of optimization are presented. Then the algorithm proposes a new definition of the position vector of air parcel, and brings a good discretization interpretation of continuous WDO. For multiobjective optimization, the grey relational grade (GRG) is then used to measure the similarity between the best two solutions for these two objectives. The best pressure locations with the maximum GRG will be recorded as the best two candidate solutions to the problem, and a final optimization result will be selected according to the importance of the two objectives. Finally, the proposed improved WDO has been applied for the optimal design of beamforming of the opportunistic antenna array, which needs a trade-off between the 3 dB main beam width and sidelobe level. The simulation results show that the proposed method outperforms conventional particle swarm optimization (PSO) in the optimal beamforming by achieving more reduction in the sidelobe level and saving more runtime.
机译:我们提出了一种新型的二进制版本的多目标风力驱动优化(WDO),用于机会阵列雷达的发射波束成形,这被认为是一个多目标优化问题。首先,给出了发射信号模型和优化的目标函数。然后该算法提出了航空包裹位置矢量的新定义,并对连续WDO进行了很好的离散化解释。对于多目标优化,然后使用灰色关联等级(GRG)来衡量针对这两个目标的最佳两种解决方案之间的相似性。具有最大GRG的最佳压力位置将被记录为该问题的最佳两个候选解决方案,并且将根据两个目标的重要性来选择最终的优化结果。最后,所提出的改进的WDO已经被用于机会天线阵列的波束成形的最佳设计,这需要在3 dB主波束宽度和旁瓣电平之间进行权衡。仿真结果表明,该方法在降低旁瓣电平并节省更多运行时间的同时,在最佳波束形成方面优于传统的粒子群算法(PSO)。

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